The invention relates to pattern recognition and, more particularly, to pattern recognition involving computing with quantum computers.
In pattern recognition, input data is processed based on a priori knowledge in form of stored reference patterns. Recognizing input data or input patterns means classifying the input pattern depending on which one of the reference patterns resembles best the input pattern. Applications for pattern recognition include, for example, voice and speech recognition, text classification or digital image analysis.
Conventional pattern recognition is, for instance based on neural networks or particular search algorithms. Usually, the computational effort, in particular, if implemented on a computer is extremely high for such pattern recognition tasks. Employing quantum mechanics may facilitate and speed-up search applications over unsorted data significantly. Such search applications over unsorted data may also be regarded as a pattern recognition as mentioned above. The advantage of a quantum-mechanical framework is mainly due to the fact that quantum-mechanical systems can be represented by a superposition of states that can be influenced or manipulated simultaneously by quantum-mechanical operations performed on such states. It is also possible that quantum states of two or more objects are described with respect to one another. This is referred to as an entanglement of states. Quantum-mechanics based algorithms are believed to exceed the computational efficiency of traditional computers and may be implemented as quantum-mechanical simulations on conventional computers as well as physical implementations of quantum-computers in terms of quantum systems.